rm(list=ls())
libs<-c("rstan", "gdata", "bayesplot", "stringr", "dplyr", "ggplot2", "PerformanceAnalytics")
sapply(libs, require, character.only=TRUE)Loading required package: rstanLoading required package: StanHeaders
rstan version 2.26.22 (Stan version 2.26.1)For execution on a local, multicore CPU with excess RAM we recommend calling
options(mc.cores = parallel::detectCores()).
To avoid recompilation of unchanged Stan programs, we recommend calling
rstan_options(auto_write = TRUE)
For within-chain threading using `reduce_sum()` or `map_rect()` Stan functions,
change `threads_per_chain` option:
rstan_options(threads_per_chain = 1)Loading required package: gdata
Attaching package: 'gdata'The following object is masked from 'package:stats':
nobsThe following object is masked from 'package:utils':
object.sizeThe following object is masked from 'package:base':
startsWithLoading required package: bayesplotThis is bayesplot version 1.11.1- Online documentation and vignettes at mc-stan.org/bayesplot- bayesplot theme set to bayesplot::theme_default() * Does _not_ affect other ggplot2 plots * See ?bayesplot_theme_set for details on theme settingLoading required package: stringrLoading required package: dplyr
Attaching package: 'dplyr'The following objects are masked from 'package:gdata':
combine, first, last, starts_withThe following objects are masked from 'package:stats':
filter, lagThe following objects are masked from 'package:base':
intersect, setdiff, setequal, unionLoading required package: ggplot2Loading required package: PerformanceAnalyticsLoading required package: xtsLoading required package: zoo
Attaching package: 'zoo'The following objects are masked from 'package:base':
as.Date, as.Date.numeric
######################### Warning from 'xts' package ##########################
# #
# The dplyr lag() function breaks how base R's lag() function is supposed to #
# work, which breaks lag(my_xts). Calls to lag(my_xts) that you type or #
# source() into this session won't work correctly. #
# #
# Use stats::lag() to make sure you're not using dplyr::lag(), or you can add #
# conflictRules('dplyr', exclude = 'lag') to your .Rprofile to stop #
# dplyr from breaking base R's lag() function. #
# #
# Code in packages is not affected. It's protected by R's namespace mechanism #
# Set `options(xts.warn_dplyr_breaks_lag = FALSE)` to suppress this warning. #
# #
###############################################################################
Attaching package: 'xts'The following objects are masked from 'package:dplyr':
first, lastThe following objects are masked from 'package:gdata':
first, last
Attaching package: 'PerformanceAnalytics'The following object is masked from 'package:graphics':
legend rstan gdata bayesplot
TRUE TRUE TRUE
stringr dplyr ggplot2
TRUE TRUE TRUE
PerformanceAnalytics
TRUE datapath <- '/fast/work/groups/ag_schlagenhauf/B01_FP1_WP2/WP2_ILT_CODE/02_Behav_and_Comp_Modeling/'
out_path <- '/fast/work/groups/ag_schlagenhauf/B01_FP1_WP2/WP2_ILT_CODE/02_Behav_and_Comp_Modeling/Output'
behavpath <- '/fast/work/groups/ag_schlagenhauf/B01_FP1_WP2/ILT_DATA'
# load files containing true parameters used as input for simulation
orig_file <- 'fit_n58_2024-05-07_bandit2arm_delta_PH_withC_DU_estimation1_delta0.999_stepsize0.1_treedepth12.rds'
orig_fit <- readRDS(file.path(out_path, orig_file)) # Stan model output
# load simulation output file containing y_pred and transformed parameters
sim_file <- 'sim_2024-05-07_bandit2arm_delta_PH_withC_sim_n58.rds'
sim_fit <- readRDS(file.path(out_path, 'Parameter_Recovery', sim_file)) # Stan model output
# load simulated data fitting results
recovery_file <- 'recovery_2024-05-10_bandit2arm_delta_PH_withC_n58.rds'
recovery_fit <- readRDS(file.path(out_path, 'Parameter_Recovery', recovery_file)) # Stan model output
color_scheme_set("mix-blue-pink")
